Combining SchNet and SHARC: The SchNarc machine learning approach for
excited-state dynamics

Combining SchNet and SHARC: The SchNarc machine learning approach for excited-state dynamics

17 February 2020

Julia Westermayr

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Papers citing "Combining SchNet and SHARC: The SchNarc machine learning approach for excited-state dynamics"

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Title
A practical guide to machine learning interatomic potentials -- Status and future Ryan Jacobs D. Morgan Siamak Attarian Jun Meng Chen Shen ... K. J. Schmidt So Takamoto Aidan Thompson Julia Westermayr Brandon M. Wood 113 9 0 12 Mar 2025
Collaborative Goal Tracking of Multiple Mobile Robots Based on Geometric Graph Neural Network Qingquan Lin Weining Lu 71 1 0 13 Nov 2023
HOAX: A Hyperparameter Optimization Algorithm Explorer for Neural Networks Albert S. Thie M. Menger S. Faraji 53 0 0 01 Feb 2023
Graph neural networks for materials science and chemistry Patrick Reiser Marlen Neubert André Eberhard Luca Torresi Chen Zhou ... Houssam Metni Clint van Hoesel Henrik Schopmans T. Sommer Pascal Friederich GNN AI4CE 125 422 0 05 Aug 2022
Excited state, non-adiabatic dynamics of large photoswitchable molecules using a chemically transferable machine learning potential Simon Axelrod E. Shakhnovich Rafael Gómez-Bombarelli 101 53 0 10 Aug 2021
Accurate Prediction of Free Solvation Energy of Organic Molecules via Graph Attention Network and Message Passing Neural Network from Pairwise Atomistic Interactions Ramin Ansari Amirata Ghorbani 46 1 0 15 Apr 2021
Implementing graph neural networks with TensorFlow-Keras Patrick Reiser André Eberhard Pascal Friederich GNN 81 16 0 07 Mar 2021
Equivariant message passing for the prediction of tensorial properties and molecular spectra Kristof T. Schütt Oliver T. Unke M. Gastegger 118 545 0 05 Feb 2021
Machine learning of solvent effects on molecular spectra and reactions M. Gastegger Kristof T. Schütt Klaus-Robert Muller AI4CE 71 62 0 28 Oct 2020
Machine Learning Force Fields Oliver T. Unke Stefan Chmiela H. E. Sauceda M. Gastegger I. Poltavsky Kristof T. Schütt A. Tkatchenko K. Müller AI4CE 143 940 0 14 Oct 2020
Deep Learning for UV Absorption Spectra with SchNarc: First Steps Towards Transferability in Chemical Compound Space Julia Westermayr P. Marquetand 91 53 0 15 Jul 2020
Machine learning for electronically excited states of molecules Julia Westermayr P. Marquetand 71 266 0 10 Jul 2020
Machine learning and excited-state molecular dynamics Julia Westermayr P. Marquetand AI4CE 61 56 0 28 May 2020
Representations of molecules and materials for interpolation of quantum-mechanical simulations via machine learning Marcel F. Langer Alex Goessmann M. Rupp AI4CE 73 99 0 26 Mar 2020
Neural networks and kernel ridge regression for excited states dynamics of CH $_2$ NH $_2^+$ : From single-state to multi-state representations and multi-property machine learning models Julia Westermayr Felix A Faber Anders S. Christensen O. von Lilienfeld P. Marquetand 44 40 0 18 Dec 2019